Multi-agent swarm orchestrator for AI workflows
Network-AI
TypeScript/Node.js multi-agent orchestrator — shared state, guardrails, budgets, and cross-framework coordination
Network-AI is a TypeScript/Node.js multi-agent orchestrator that adds coordination, guardrails, and governance to any AI agent stack.
- Shared blackboard with locking — atomic
propose → validate → commitprevents race conditions and split-brain failures across parallel agents - Guardrails and budgets — FSM governance, per-agent token ceilings, HMAC / Ed25519 audit trails, and permission gating
- 17 adapters — LangChain (+ streaming), AutoGen, CrewAI, OpenAI Assistants, LlamaIndex, Semantic Kernel, Haystack, DSPy, Agno, MCP, Custom (+ streaming), OpenClaw, A2A, Codex, MiniMax, NemoClaw, and APS — no glue code, no lock-in
- Persistent project memory (Layer 3) —
context_manager.pyinjects decisions, goals, stack, milestones, and banned patterns into every system prompt so agents always have full project context
The silent failure mode in multi-agent systems: parallel agents writing to the same key use last-write-wins by default — one agent's result silently overwrites another's mid-flight. The outcome is split-brain state: double-spends, contradictory decisions, corrupted context, no error thrown. Network-AI's
propose → validate → commitmutex prevents this at the coordination layer, before any write reaches shared state.
Use Network-AI as:
- A TypeScript/Node.js library —
import { createSwarmOrchestrator } from 'network-ai' - An MCP server —
npx network-ai-server --port 3001 - A CLI —
network-ai bb get status/network-ai audit tail - An OpenClaw skill —
clawhub install network-ai
**5-minute quickstart →** | **Architecture →** | **All adapters →** | **Benchmarks →**
⚡ Try in 60 Seconds
npm install network-ai
import { LockedBlackboard } from 'network-ai';
const board = new LockedBlackboard('.');
const id = board.propose('status', { ready: true }, 'agent-1');
board.validate(id, 'agent-1');
board.commit(id);
console.log(board.read('status')); // { ready: true }
Two agents, atomic writes, no race conditions. That's it.
Want the full stress test? No API key, ~3 seconds:
npx ts-node examples/08-control-plane-stress-demo.ts
Runs priority preemption, AuthGuardian permission gating, FSM governance, and compliance monitoring — all without a single LLM call.
If it saves you from a race condition, a ⭐ helps others find it.
What's Included
| ✅ Atomic shared state | propose → validate → commit with filesystem mutex — no split-brain |
| ✅ Token budgets | Hard per-agent ceilings with live spend tracking |
| ✅ Permission gating | HMAC / Ed25519-signed tokens, scoped per agent and resour |
Tools (3)
blackboard_readRead data from the shared blackboardblackboard_writePropose and commit data to the shared blackboardaudit_logRetrieve audit logs for agent activitiesEnvironment Variables
NETWORK_AI_PORTPort for the MCP server to listen onConfiguration
{"mcpServers": {"network-ai": {"command": "npx", "args": ["-y", "network-ai-server"]}}}